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Dual-Layer Fusion Knowledge Reasoning with Enhanced Multi-modal Features [PDF]
Jisuanji kexue yu tansuoMost of the existing multi-modal knowledge reasoning methods use splicing or attention to directly fuse the multi-modal features extracted from the pre-trained model, often ignoring the heterogeneity and interaction complexity between different modes ...
JING Boxiang, WANG Hairong, WANG Tong, YANG Zhenye
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Deep Multi-Semantic Fusion-Based Cross-Modal Hashing
Mathematics, 2022 Due to the low costs of its storage and search, the cross-modal retrieval hashing method has received much research interest in the big data era. Due to the application of deep learning, the cross-modal representation capabilities have risen markedly ...
Xinghui Zhu +3 more
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Visual Question Answering Model Based on Multi-modal Deep Feature Fusion [PDF]
Jisuanji kexue, 2023 In the era of big data,with the explosive growth of multi-source heterogeneous data,multi-modal data fusion has attracted much attention of researchers,and visual question answering(VQA) has become a hot topic in multi-modal data fusion due to its image ...
ZOU Yunzhu, DU Shengdong, TENG Fei, LI Tianrui
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Robust multi-modal and multi-unit feature level fusion of face and iris biometrics [PDF]
, 2008 Multi-biometrics has recently emerged as a mean of more robust and effcient personal verification and identification. Exploiting information from multiple sources at various levels i.e., feature, score, rank or decision, the false acceptance and ...
Rattani, Ajita, Tistarelli, Massimo
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Efficient Multi-Modal Fusion with Diversity Analysis [PDF]
Proceedings of the 29th ACM International Conference on Multimedia, 2021 Multi-modal machine learning has been a prominent multi-disciplinary research area since its success in complex real-world problems. Empirically, multi-branch fusion models tend to generate better results when there is a high diversity among each branch of the model.
Shuhui Qu, Yan Kang, Janghwan Lee
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RGB-T salient object detection via fusing multi-level CNN features [PDF]
, 2019 RGB-induced salient object detection has recently witnessed substantial progress, which is attributed to the superior feature learning capability of deep convolutional neural networks (CNNs).
Han, Jungong +5 more
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Feature-Fusion Guidelines for Image-Based Multi-Modal Biometric Fusion
South African Computer Journal, 2017 The feature level, unlike the match score level, lacks multi-modal fusion guidelines. This work demonstrates a new approach for improved image-based biometric feature-fusion. The approach extracts and combines the face, fingerprint and palmprint at the feature level for improved human identification accuracy.
Brown, Dane L, Bradshaw, Karen L
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Multi-modal Medical Volumes Fusion by Surface Matching [PDF]
ISSPA '99. Proceedings of the Fifth International Symposium on Signal Processing and its Applications (IEEE Cat. No.99EX359), 1999 Presents a fast, six degrees of freedom, registration technique to accurately locate the position and orientation of medical volumes (e.g. CT, MRI) with respect to each other for the same patient. The technique uses surface registration and maximization of mutual information.
A.M. Eldeib, S.M. Yamany, A. Farag
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Noncontact Sleep Study by Multi-Modal Sensor Fusion [PDF]
Sensors, 2017 Polysomnography (PSG) is considered as the gold standard for determining sleep stages, but due to the obtrusiveness of its sensor attachments, sleep stage classification algorithms using noninvasive sensors have been developed throughout the years. However, the previous studies have not yet been proven reliable.
Ku-young Chung +5 more
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Exponential Multi-Modal Discriminant Feature Fusion for Small Sample Size
IEEE Access, 2022 Multi-modal Canonical Correlation Analysis (MCCA) is an important information fusion method, and some discriminant variations of MCCA have been proposed.
Yanmin Zhu, Tianhao Peng, Shuzhi Su
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